Single Snapshot Multi-angle Target 2D Reconstruction based on RANSAC and RAM

Single snapshot multi-angle fusion radar target reconstruction refers to the real-time reconstruction of the target by using the observation data of a single snapshot and combining the radar observation data of multiple angles. Based on the geometric projection relationship of the target scattering center in the radar line-of-sight, this paper uses the random sample consensus (RANSAC) method to realize the detection of the validity of the scattering center correlation samples, associate the scattering centers based on multi-angle high resolution range profile (HRRP). Next, the multi-station data is applied to the association output of RANSAC for the target reconstruction process, which is very sensitive to the distance and angle measurement error of multiple stations. To deal with distance error, the reweighted atomic norm minimization (RAM) to realize the super-resolution. The angle measurements error is calibrated by the fused centroid as the distance alignment reference point. The bistatic geometry between every two stations further improves the reconstruction accuracy; hence, the number of stations can be reduced. The performance of the proposed methods is verified by the simulation results.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/radar58436.2024.10993548
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single Snapshot Multi-angle Target 2D Reconstruction based on RANSAC and RAM

Hui Ma, Hongwei Liu, Xiao Chaoshen
Advanced Optical Sensing Technologies
article

Single Snapshot Multi-angle Target 2D Reconstruction based on RANSAC and RAM

Hui Ma, Hongwei Liu, Xiao Chaoshen
article en

Abstract

Single snapshot multi-angle fusion radar target reconstruction refers to the real-time reconstruction of the target by using the observation data of a single snapshot and combining the radar observation data of multiple angles. Based on the geometric projection relationship of the target scattering center in the radar line-of-sight, this paper uses the random sample consensus (RANSAC) method to realize the detection of the validity of the scattering center correlation samples, associate the scattering centers based on multi-angle high resolution range profile (HRRP). Next, the multi-station data is applied to the association output of RANSAC for the target reconstruction process, which is very sensitive to the distance and angle measurement error of multiple stations. To deal with distance error, the reweighted atomic norm minimization (RAM) to realize the super-resolution. The angle measurements error is calibrated by the fused centroid as the distance alignment reference point. The bistatic geometry between every two stations further improves the reconstruction accuracy; hence, the number of stations can be reduced. The performance of the proposed methods is verified by the simulation results.

Xidian University (CN)
Sustainable cities and communities
Openalex Percentile: Top 78%
Advanced Optical Sensing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.